# Calculate mean and median buyrate for each stance buyrate_avg1 = fb.groupby('EITHER_CHAMP')['Avg_Buyrate_Per_Event'].agg(['mean', 'median']) # Display the statistics buyrate_avg1
# Calculate mean and median buyrate for each stance buyrate_avg2 = fb.groupby('EVER_CHALLENGER')['Avg_Buyrate_Per_Event'].agg(['mean', 'median']) # Display the statistics buyrate_avg2
### Top 1 Percent
# Filter the dataframe using the correct column name "FIGHTER" frame_1 = subset_df[subset_df['FIGHTER'].isin(top_1_percent_list)] frame_1frame_1.describe()